In this Kedro project, we aim to scrape real estate data from the website Ouedkniss in order to create a machine learning model that estimate the price of a real estate. This project also integrate the DagHub MLOps technology (see https://dagshub.com/anismhaddouche/ouedkniss-kedro).
To get an overview of the pipeline structure in this project, run :
kedro viz --load-file my_shareable_pipeline.json
Declare any dependencies in src/requirements.txt for pip installation and src/environment.yml for conda installation.
To install them, run:
pip install -r src/requirements.txt
You can run this Kedro project with:
kedro run
Have a look at the file src/tests/test_run.py for instructions on how to write the tests. You can run your tests as follows:
kedro test
To configure the coverage threshold, go to the .coveragerc file.
To generate or update the dependency requirements for your project:
kedro build-reqs
This will pip-compile the contents of src/requirements.txt into a new file src/requirements.lock. You can see the output of the resolution by opening src/requirements.lock.
After this, if you'd like to update your project requirements, please update src/requirements.txt and re-run kedro build-reqs.
Further information about project dependencies
Note: Using
kedro jupyterorkedro ipythonto run your notebook provides these variables in scope:context,catalog, andstartup_error.Jupyter, JupyterLab, and IPython are already included in the project requirements by default, so once you have run
pip install -r src/requirements.txtyou will not need to take any extra steps before you use them.
To use Jupyter notebooks in your Kedro project, you need to install Jupyter:
pip install jupyter
After installing Jupyter, you can start a local notebook server:
kedro jupyter notebook
To use JupyterLab, you need to install it:
pip install jupyterlab
You can also start JupyterLab:
kedro jupyter lab
And if you want to run an IPython session:
kedro ipython
You can move notebook code over into a Kedro project structure using a mixture of cell tagging and Kedro CLI commands.
By adding the node tag to a cell and running the command below, the cell's source code will be copied over to a Python file within src/<package_name>/nodes/:
kedro jupyter convert <filepath_to_my_notebook>
Note: The name of the Python file matches the name of the original notebook.
Alternatively, you may want to transform all your notebooks in one go. Run the following command to convert all notebook files found in the project root directory and under any of its sub-folders:
kedro jupyter convert --all
To automatically strip out all output cell contents before committing to git, you can run kedro activate-nbstripout. This will add a hook in .git/config which will run nbstripout before anything is committed to git.
Note: Your output cells will be retained locally.